Friday, March22 Session 3: Brain Development/Disorder

Arvind Kumar
KTH Royal Institute of Technology

Title
Computational approaches to understand on brain diseases
Abstract
Brain diseases provides a unique window to understand brain function andidentify crucial components of the neural hardware and neuronal activity
dynamics that shape the brain function. Traditionally, much focus has been on
identifying genetic, morphological or chemical causes of brain dysfunction.
However, there is no one to one mapping between genetic/chemical changes andsymptoms of brain diseases. Indeed, similar genetic mutations and chemical
imbalances can result in very different behavioural deficits. In recent years,accumulating experimental evidence has suggested that independent of their
genetic, biochemical, or morphological origins, behavioural symptoms of many
brain disease (e.g. Epilepsy, Parkinson’s disease, anxiety) are causally associatedwith changes in the electrical activity of the brain. When the disease-related
activity is restored to normal levels (by brain stimulation), some of the symptomsof the disease are also alleviated. These observations have led to thedevelopment of computational approaches to understand brain diseases which
are rooted either in the dynamical systems theory or decision-making andreinforcement learning. In my talk I will describe how brain diseases can beunderstood as diseases of brain dynamics or information processing. I will discuss
recent progress in modelling of the aberrant activity in Parkinson’s disease andanxiety. For both diseases, we investigated how low-level changes in the neuron
excitability and synaptic connectivity lead to changes in network dynamics in thebasal ganglia and amygdala and eventually high-level disease-specific functional
deficits. Interestingly this investigation revealed common network mechanisms

shared by the two diseases. Finally, I will describe a closed-loop stimulation
strategy that uses minimal stimulation to not only change the brain activity state
to normal levels but also recovers the network computations lost due to thedisease condition.

Biography
Arvind Kumar is an Associate Professor of Computational Neuroscience andNeuroinformatics at the KTH Royal Institute of Technology, Stockholm Sweden.
He is interested understanding dynamical properties and information processingin spiking activity in neuronal networks. In particular, his research group isinvestigating the functional and dynamical consequences of neuronal diversity
and how does the interplay of network connectivity and network dynamics affectthe transfer of information across networks? In addition, he is developing
computational models of brain disorders and neuralizing the control systemtheory to develop tools for the control of neural dynamics using brain stimulation
methods.
Arvind Kumar studied electrical and electronics engineering and obtained aMasters in Engineering degree from the Birla Institute of Technology and Science,
Pilani, India. He then worked at the Indian Institute of Technology, New Delhi,
India, as a Senior Research Fellow. He was exposed to computational
neuroscience at the RIKEN Brain Science summer school. In 2006 he obtained aPh.D. in computational neuroscience under the supervision of Ad Aertsen andStefan Rotter, at the University in Freiburg, Germany. He did his post-doctoral
training with Mayank Mehta at the Brown University, Providence, USA.
He spends his free time either playing Cricket or analyzing Cricket related data.